Summary

Dataset 1

Experiments excluded

Mask

Get figure file: figures/preliminary_dset-1_figure-mask.png

Peak coordinates

Get figure file: figures/preliminary_dset-1_figure-static.png
Get figure file: figures/preliminary_dset-1_figure-legend.png

Explorer

Meta-Analysis

Estimator

Parameters use to fit the meta-analytic estimator.

Corrector

Parameters use to fit the corrector.

Corrected meta-analytic map: z_corr-FDR_method-indep

Explorer

The following figure provides an interactive window to explore the meta-analytic map in detail.

Slice viewer

This panel shows the the corrrected meta-analytic map.

Get figure file: figures/corrector_figure-static.png

Diagnostics

Target image: z_corr-FDR_method-indep

Significant clusters

    X Y Z Peak Stat Cluster Size (mm3)
Tail Cluster ID          
Positive 1 0.00 -58.00 30.00 10.31 12360
1a -2.00 -52.00 22.00 7.61
1b 2.00 -52.00 48.00 2.75
1c -10.00 -52.00 18.00 2.46
2 -48.00 -62.00 24.00 8.47 46480
2a -52.00 -56.00 18.00 7.39
2b -46.00 -58.00 32.00 7.17
2c -46.00 -70.00 12.00 6.27
3 54.00 -44.00 12.00 7.61 32632
3a 58.00 -48.00 18.00 6.95
3b 46.00 -68.00 6.00 6.27
3c 50.00 -52.00 20.00 6.04
4 -2.00 56.00 22.00 7.17 35496
4a 0.00 16.00 52.00 6.95
4b -4.00 8.00 54.00 6.50
4c 2.00 20.00 48.00 5.81
5 -42.00 20.00 -8.00 6.50 9952
5a -46.00 26.00 -14.00 6.27
5b -36.00 18.00 0.00 6.04
5c -50.00 32.00 -10.00 5.81
6 56.00 -2.00 -16.00 6.27 8536
6a 54.00 2.00 -24.00 5.09
6b 54.00 -16.00 -12.00 3.31
6c 48.00 -10.00 -18.00 3.03
7 48.00 16.00 32.00 5.33 17160
7a 38.00 24.00 -6.00 4.86
7b 48.00 26.00 0.00 4.86
7c 52.00 26.00 8.00 4.61
8 -42.00 6.00 48.00 4.36 8696
8a -48.00 32.00 18.00 3.58
8b -50.00 28.00 26.00 3.58
8c -40.00 6.00 34.00 3.58
9 16.00 -26.00 -2.00 4.11 1984
9a 22.00 -30.00 -6.00 2.75
9b 10.00 -18.00 4.00 2.18
9c 22.00 -26.00 -4.00 2.18
10 14.00 10.00 0.00 3.58 2000
10a 12.00 16.00 -6.00 3.03
10b 12.00 4.00 4.00 3.03
10c 16.00 6.00 -4.00 3.03
11 36.00 -54.00 44.00 3.31 2192
11a 24.00 -66.00 58.00 2.75
11b 32.00 -62.00 48.00 2.75
11c 40.00 -60.00 46.00 2.75
12 -26.00 -4.00 56.00 3.31 960
12a -32.00 -8.00 52.00 2.46
13 -24.00 -28.00 -2.00 3.31 904
14 -10.00 10.00 0.00 3.03 1296
14a -14.00 4.00 -6.00 2.75
14b -14.00 2.00 6.00 2.75
14c -6.00 10.00 0.00 2.75
15 -6.00 -84.00 -6.00 2.75 464
15a -6.00 -90.00 0.00 2.46
15b -2.00 -82.00 -2.00 2.46
15c -10.00 -82.00 -8.00 2.18
16 -10.00 -88.00 10.00 2.75 104
17 26.00 -6.00 -20.00 2.75 368
18 -54.00 6.00 20.00 2.46 1056
18a -52.00 6.00 12.00 2.46
18b -52.00 8.00 20.00 2.46
18c -52.00 10.00 12.00 2.46
19 -22.00 -68.00 48.00 2.46 240
20 38.00 -34.00 48.00 2.46 280
20a 44.00 -32.00 58.00 2.46
20b 42.00 -30.00 48.00 2.18
21 -34.00 14.00 44.00 2.18 80
22 -12.00 -54.00 10.00 2.18 168
23 -30.00 -56.00 -20.00 2.18 96
24 -20.00 -78.00 -34.00 1.88 104

Label map: positive tail

Get figure file: figures/diagnostics_tail-positive_figure.png

FocusCounter

The FocusCounter analysis characterizes the relative contribution of each experiment in a meta-analysis to the resulting clusters by counting the number of peaks from each experiment that fall within each significant cluster.

The heatmap presents the relative contributions of each experiment to each cluster in the thresholded map. There is one row for each experiment, and one column for each cluster, with column names being PostiveTail/NegativeTail indicating the sign (+/-) of the cluster's statistical values. The rows and columns were re-ordered to form clusters in the heatmap.

Heatmap: positive tail

Methods

We kindly ask to report results preprocessed with this tool using the following boilerplate.

A multilevel kernel density (MKDA) meta-analysis \citep{wager2007meta} was performed was performed
with NiMARE 0.6.0+6.g55f7ea1 (RRID:SCR_017398; \citealt{Salo2023}), using a(n) MKDA kernel. An MKDA
kernel \citep{wager2007meta} was used to generate study-wise modeled activation maps from
coordinates. In this kernel method, each coordinate is convolved with a sphere with a radius of
10.0 and a value of 1. For voxels with overlapping spheres, the maximum value was retained. Summary
statistics (OF values) were converted to p-values using an approximate null distribution. The input
dataset included 3296 foci from 405 experiments. False discovery rate correction was performed with
the Benjamini-Hochberg procedure \citep{benjamini1995controlling}.

Bibliography

@article{Salo2023,
  doi = {10.52294/001c.87681},
  url = {https://doi.org/10.52294/001c.87681},
  year = {2023},
  volume = {3},
  pages = {1 - 32},
  author = {Taylor Salo and Tal Yarkoni and Thomas E. Nichols and Jean-Baptiste Poline and Murat Bilgel and Katherine L. Bottenhorn and Dorota Jarecka and James D. Kent and Adam Kimbler and Dylan M. Nielson and Kendra M. Oudyk and Julio A. Peraza and Alexandre Pérez and Puck C. Reeders and Julio A. Yanes and Angela R. Laird},
  title = {NiMARE: Neuroimaging Meta-Analysis Research Environment},
  journal = {Aperture Neuro}
}
@article{benjamini1995controlling,
  title={Controlling the false discovery rate: a practical and powerful approach to multiple testing},
  author={Benjamini, Yoav and Hochberg, Yosef},
  journal={Journal of the Royal statistical society: series B (Methodological)},
  volume={57},
  number={1},
  pages={289--300},
  year={1995},
  publisher={Wiley Online Library},
  url={https://doi.org/10.1111/j.2517-6161.1995.tb02031.x},
  doi={10.1111/j.2517-6161.1995.tb02031.x}
}
@article{wager2007meta,
  title={Meta-analysis of functional neuroimaging data: current and future directions},
  author={Wager, Tor D and Lindquist, Martin and Kaplan, Lauren},
  journal={Social cognitive and affective neuroscience},
  volume={2},
  number={2},
  pages={150--158},
  year={2007},
  publisher={Oxford University Press},
  url={https://doi.org/10.1093/scan/nsm015},
  doi={10.1093/scan/nsm015}
}